RoboTwin / tactile_tasks /run_collection.py
Fxxkrobotics's picture
Add files using upload-large-folder tool
5a6766e verified
#!/usr/bin/env python3
"""
Batch data collection for tactile manipulation tasks.
Collects episodes with randomized object placements, saves per-episode HDF5 files,
and generates per-episode MP4 videos with tactile overlays.
File structure:
tactile_data/
precision_grasp/
episode_00.hdf5
episode_01.hdf5
...
peg_insertion/
episode_00.hdf5
...
gentle_stack/
episode_00.hdf5
...
videos/
precision_grasp/
precision_grasp_ep00.mp4
...
Usage:
# Collect all tasks, 50 episodes each
python tactile_tasks/run_collection.py --n_episodes 50
# Collect single task
python tactile_tasks/run_collection.py --task peg_insertion --n_episodes 50
# With visualization window (slower)
python tactile_tasks/run_collection.py --task gentle_stack --n_episodes 10 --visualize
# Custom output directory
python tactile_tasks/run_collection.py --save_dir ./my_data --n_episodes 20
# Skip video generation (faster)
python tactile_tasks/run_collection.py --n_episodes 50 --no_video
"""
import os
import sys
import argparse
import time
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from tactile_tasks.collect_data import collect_task_data, TASK_CONFIGS
from tactile_tasks.visualize_data import generate_video
def generate_all_episode_videos(task_dir, n_episodes, video_dir, task_name):
"""Generate videos for all episodes in a task directory."""
os.makedirs(video_dir, exist_ok=True)
for ep_idx in range(n_episodes):
data_file = os.path.join(task_dir, f"episode_{ep_idx:02d}.hdf5")
video_path = os.path.join(video_dir, f"{task_name}_ep{ep_idx:02d}.mp4")
if os.path.exists(video_path):
continue # skip already generated
if not os.path.exists(data_file):
print(f" Warning: {data_file} not found, skipping video")
continue
try:
generate_video(data_file, output_path=video_path)
except Exception as e:
print(f" Warning: video for episode {ep_idx} failed: {e}")
def main():
parser = argparse.ArgumentParser(description="Collect tactile manipulation data")
parser.add_argument("--task", type=str, default="all",
choices=list(TASK_CONFIGS.keys()) + ["all"],
help="Task to collect (default: all)")
parser.add_argument("--n_episodes", type=int, default=50,
help="Number of episodes per task (default: 50)")
parser.add_argument("--save_dir", type=str, default="./tactile_data",
help="Output directory (default: ./tactile_data)")
parser.add_argument("--visualize", action="store_true",
help="Show renderer window during collection")
parser.add_argument("--no_video", action="store_true",
help="Skip video generation")
args = parser.parse_args()
tasks = list(TASK_CONFIGS.keys()) if args.task == "all" else [args.task]
total_start = time.time()
for task in tasks:
print(f"\n{'='*60}")
print(f" Collecting: {task} | {args.n_episodes} episodes")
print(f"{'='*60}")
t0 = time.time()
task_dir = collect_task_data(
task,
n_episodes=args.n_episodes,
save_dir=args.save_dir,
visualize=args.visualize,
)
elapsed = time.time() - t0
print(f" Collection time: {elapsed:.0f}s ({elapsed/args.n_episodes:.1f}s/ep)")
if not args.no_video:
print(f"\n Generating videos...")
video_dir = os.path.join(args.save_dir, "videos", task)
generate_all_episode_videos(task_dir, args.n_episodes, video_dir, task)
print(f" Videos saved to: {video_dir}/")
total_elapsed = time.time() - total_start
print(f"\n{'='*60}")
print(f" Done! Total time: {total_elapsed:.0f}s")
print(f" Data saved to: {args.save_dir}/")
print(f"{'='*60}")
if __name__ == "__main__":
main()